Fragment-based modeling of membrane protein loops: successes, failures, and prospects for the future

Proteins. 2014 Feb;82(2):175-86. doi: 10.1002/prot.24299. Epub 2013 Oct 17.

Abstract

Membrane proteins (MPs) have become a major focus in structure prediction, due to their medical importance. There is, however, a lack of fast and reliable methods that specialize in the modeling of MP loops. Often methods designed for soluble proteins (SPs) are applied directly to MPs. In this article, we investigate the validity of such an approach in the realm of fragment-based methods. We also examined the differences in membrane and soluble protein loops that might affect accuracy. We test our ability to predict soluble and MP loops with the previously published method FREAD. We show that it is possible to predict accurately the structure of MP loops using a database of MP fragments (0.5-1 Å median root-mean-square deviation). The presence of homologous proteins in the database helps prediction accuracy. However, even when homologues are removed better results are still achieved using fragments of MPs (0.8-1.6 Å) rather than SPs (1-4 Å) to model MP loops. We find that many fragments of SPs have shapes similar to their MP counterparts but have very different sequences; however, they do not appear to differ in their substitution patterns. Our findings may allow further improvements to fragment-based loop modeling algorithms for MPs. The current version of our proof-of-concept loop modeling protocol produces high-accuracy loop models for MPs and is available as a web server at http://medeller.info/fread.

Keywords: FREAD; MEDELLER; PyFREAD; database loop structure prediction; homology modeling.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acid Motifs
  • Computer Simulation*
  • Databases, Protein
  • Membrane Proteins / chemistry*
  • Models, Molecular*
  • Peptide Fragments / chemistry*
  • Software
  • Structural Homology, Protein

Substances

  • Membrane Proteins
  • Peptide Fragments